RandLA-Net
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Test point cloud with pretrained model
Hello, I want to use the point cloud I collected to test the pre-trained model on semanticKITTI. I just convert the ply file to .npy and put it in velodyne, but it will show that the array is out of bounds. I need to run dataset prepare to generate a new KDTree and proj files?

do you used unlabled data to predit? and you have solved it ?